The predictive link between matrix and metastasis
The predictive link between matrix and metastasis
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DOI：
10.1016/j.coche.2016.01.001
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发表时间：
2016-02-01
影响因子：
6.6
通讯作者：
Peyton, S. R.
中科院分区：
文献类型：
--
作者：
Barney, L. E.;Jansen, L. E.;Peyton, S. R.
癌症扩散（转移）是90%的癌症相关死亡的原因。告知患者治疗以防止转移，或在患者体内的所有癌细胞转移之前杀死它们是非常强大的。然而，对所有非转移性患者的积极治疗是有害的，无论是对生活质量的关注，还是肾脏或肝脏相关毒性的风险。了解患者何时何地有转移风险可能会彻底改变患者的治疗和护理。在这篇综述中，我们试图总结工程师和定量生物学家在开发预测转移的策略和模型系统方面的关键工作，特别关注细胞与细胞外基质（ECM）的相互作用，作为预测转移风险和向性的工具。
Cancer spread (metastasis) is responsible for 90% of cancer-related fatalities. Informing patient treatment to prevent metastasis, or kill all cancer cells in a patient's body before it becomes metastatic is extremely powerful. However, aggressive treatment for all non-metastatic patients is detrimental, both for quality of life concerns, and the risk of kidney or liver-related toxicity. Knowing when and where a patient has metastatic risk could revolutionize patient treatment and care. In this review, we attempt to summarize the key work of engineers and quantitative biologists in developing strategies and model systems to predict metastasis, with a particular focus on cell interactions with the extracellular matrix (ECM), as a tool to predict metastatic risk and tropism.